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진주시 화재발생 패턴분석과 위험등급 산출

Fire Occurrence Pattern Analysis and Fire Risk Calculation of Jinju City

  • Bae, Gyu Han (Urban engineering, Gyeongsang National University) ;
  • Yoo, Hwan Hee (Urban engineering, Gyeongsang National University)
  • 투고 : 2014.11.28
  • 심사 : 2014.12.16
  • 발행 : 2014.12.31

초록

급속한 도시성장에 따라 도시지역에는 다양하고 복잡한 시설물들이 증가되고 있으며, 이에 따른 화재발생 피해에 대한 위험도도 증가되고 있다. 특히 화재사고는 인위적 재해 중 교통사고와 함께 도시지역에서 가장 높은 발생빈도를 나타내고 있다. 이에 따라 소방방재청에서는 효과적인 화재관리를 위하여 국가화재정보시스템을 운영하고 있으며 2007년부터 화재발생정보를 인터넷을 통해 제공하고 있다. 따라서 본 연구에서는 이 시스템에서 제공하는 데이터와 진주시 소방서로부터 자료를 취득하여 진주시 화재데이터베이스를 구축하고, 2007년부터 2013년까지 화재발생 추이에 대한 시계열분석과 Moran's I, Getis-Ord $Gi^*$분석을 통하여 진주시 공간상의 화재발생 밀도변화분석과 시설물별 화재위험도를 산출하였다. 그 결과 화재발생위치의 시계열적 변화와 화재발생 밀집도가 높은 Hot Spot지역을 추출할 수 있었으며, 시설물별 인명피해 및 재산피해 매트릭스를 작성하여 화재위험등급을 산출함으로서 도시지역의 화재발생위험을 예측할 수 있는 방안을 제시하였다.

Diverse and complex facilities have been on the increase in urban areas in accordance with rapid urbanization. Along the lines of the increase in facilities, the risk of fire has increased. In particular, fire accidents as well as traffic accidents accounted for the highest rate in artificial disasters. Therefore, the National Fire Information Systems managed by the National Emergency Management Agency (NEMA) appeared for the effective fire management. The NEMA has provided the public with the Internet services regarding information about fire outbreak since 2007. This study acquired data from both NEMA and the Jinju City Fire Department. It constructed the fire data of Jinju City and calculated the change in spatial density targeting fire, occurred in Jinju city with a view to examining the fire risk of facilities by conducting a time series analysis on the trends of fire outbreak over a span of periods between 2007 and 2013. It also conducted an analysis of Moran's I, Getis-Ord Gi. Therefore, it came to select higher hot spots in terms of fire location and fire density. In addition, it attempted to calculate the levels of fire hazard by drawing up the matrix of personal injury and property damage, depending on facilities to present the methods, which can predict the risk of fire occurrence in urban areas.

키워드

참고문헌

  1. Bae, G. and Yoo, H. 2014, Fire characteristics analysis of urban facilities in jinju, Journal of the Korean Society for Geospatial Information System, pp. 73-74.
  2. Bae, G. and Yoo, H. 2014, Fire risk assessment on the land use zoning in Korea, Proc. of the 35th Asian Conference on Remote Sensing, CD, file no. PS-048.
  3. Brian, J.M., 2002, Building fire risk analysis, the Society of Fire Protection Engineers copyright, SEPE Handbook of Fire Protection Engineering, pp. Sec. 5.153-175.
  4. Chung, U. 2009, A study on the development of risk index for the fire risk assessment of the buildings, Myeongji University Graduate School.
  5. Jung, D. and Son, Y. 2009, A analysis on the spatial features of the neighborhood trade area using positive spatial autocorrelation method, Journal of the Korean Society for Geospatial Information System, Vol, 17. No. 1, pp. 141-147.
  6. Shin, J., Jeong, S., Kim, M. and Kim, H. 2012, Analysis of fire risk with building use type using statistical data, Journal of the Korea Society of Hazard Mitigation, Vol, 12. No. 4, pp. 107-114. https://doi.org/10.9798/KOSHAM.2012.12.4.107

피인용 문헌

  1. An Analysis on the Distribution Patterns of Fire Occurrence in Cheongju City Using the Spatial Statistics Method vol.15, pp.5, 2015, https://doi.org/10.9798/KOSHAM.2015.15.5.47
  2. 공간분석·데이터마이닝 융합방법론을 통한 산업안전 취약지 등급화 방안 vol.40, pp.4, 2014, https://doi.org/10.11627/jkise.2017.40.4.147